Microsoft · 2026 Edition
A complete preparation guide written by Microsoft-certified engineers. Covers the exam format,all 5 blueprint domains, a week-by-week study plan, and proven tips for passing first time.
2–3 months
Prep time
Intermediate
Difficulty
50
Exam questions
700/1000
Pass mark
Exam code
PL-300
Full name
Microsoft Power BI Data Analyst
Vendor
Microsoft
Duration
120 minutes
Questions
50 items
Passing score
700/1000 (scaled)
Domains covered
5 blueprint domains
Recommended experience
1+ year of experience working with data; familiarity with Power BI Desktop is strongly recommended
Typical prep time
2–3 months
PL-300 earns the Microsoft Certified: Power BI Data Analyst Associate certification. It validates the ability to prepare, model, visualise, and share data insights using Power BI — one of the most in-demand skills for business intelligence roles.
Job roles this opens
Domain percentage weights are not currently available for this exam. The checklist below is still useful for planning your study.
Weeks 1–2
Prepare Data: Power Query (M language), data profiling, connecting to sources
Tip: Power Query Editor is where data transformation happens before it reaches the model. Know the common transformations: remove columns, change data types, split columns, unpivot, merge queries (JOIN equivalent), append queries (UNION equivalent). PL-300 questions frequently give a Power Query scenario and ask which transformation step achieves a result.
Weeks 3–5
Model Data: data model design, relationships, DAX fundamentals
Tip: DAX calculated columns are evaluated row-by-row at import time (stored in the model); measures are evaluated in the filter context at query time (not stored). Measures are almost always preferred for aggregations — never use a calculated column for something a measure can do.
Weeks 6–7
Visualise and Analyse Data: chart types, interactions, AI visuals, Q&A
Tip: Report-level, page-level, and visual-level filters behave differently in scope. Visual interactions (Edit interactions → Filter vs Highlight vs None) control how selecting a data point in one visual affects other visuals on the page — a common PL-300 scenario.
Weeks 8–10
Deploy and Maintain Assets: workspaces, deployment pipelines, row-level security, refresh scheduling
Tip: Row-level security (RLS) uses DAX filter expressions on a role to restrict which rows a user sees. Know how to define a static role (WHERE Country = 'UK') and a dynamic role using USERNAME() or USERPRINCIPALNAME() to filter by the logged-in user.
DAX is the most important skill for PL-300. Focus on: CALCULATE (changes filter context), FILTER (row-by-row filter), ALL/ALLEXCEPT (removes filters), RELATED (looks up across a relationship), SUMX/AVERAGEX (iterators), and time intelligence functions (DATEADD, TOTALYTD, SAMEPERIODLASTYEAR).
Star schema design for Power BI: fact tables on the many-side of relationships, dimension tables on the one-side. Bidirectional cross-filtering is powerful but should be used sparingly — it can cause ambiguous filter paths and unexpected results.
Power BI Service workspaces: My Workspace is personal (no collaboration), App Workspaces are team spaces for building and sharing. A Power BI App is a curated read-only view of workspace content shared to a broad audience.
DirectQuery vs Import mode: Import loads data into the Power BI model (fast queries, data may be stale), DirectQuery sends queries to the source in real time (always current, slower for complex DAX). Live Connection is a third option for Analysis Services and Power BI datasets.
Deployment pipelines require a Premium capacity or Premium Per User licence — they allow promotion of reports through Development → Test → Production stages with comparison and selective deployment.
Apply everything in this guide with adaptive practice questions, detailed answer explanations, and domain analytics.
Deep-dive explanations of the key topics tested on PL-300 — with exam key points and common misconceptions.